OPLA-Tool v2.0: A Tool for Product Line Architecture Design Optimization

  • Willian Marques Freire UEM
  • Mamoru Massago UEM
  • Arthur Cattaneo Zavadski UEM
  • Aline Maria Malachini UEM
  • Miotto Amaral UEM
  • Thelma Elita Colanzi UEM

Resumo


The Multi-objective Optimization Approach for Product Line Architecture Design (MOA4PLA) is the seminal approach that successfully optimizes Product Line Architecture (PLA) design using search algorithms. The tool named OPLA-Tool was developed in order to automate the use of MOA4PLA. Over time, the customization of the tool to suit the needs of new research and application scenarios led to several problems. The main problems identified in the original version of OPLA-Tool are environment configuration, maintainability and usability problems, and PLA design modeling and visualization. Such problems motivated the development of a new version of this tool: OPLA-Tool v2.0, presented in this work. In this version, those problems were solved by the source code refactoring, migration to a web-based graphical user interface (GUI) and inclusion of a new support tool for PLA modeling and visualization. Furthermore, OPLA-Tool v2.0 has new functionalities, such as new objective functions, new search operators, intelligent interaction with users during the optimization process, multi-user authentication and simultaneous execution of several experiments to PLA optimization. Such a new version of OPLA-Tool is an important achievement to PLA design optimization as it provides an easier and more complete way to automate this task.
Palavras-chave: product line architecture, Software product line, multi-objective evolutionary algorithms
Publicado
21/10/2020
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FREIRE, Willian Marques; MASSAGO, Mamoru; ZAVADSKI, Arthur Cattaneo; MALACHINI, Aline Maria; AMARAL, Miotto; COLANZI, Thelma Elita. OPLA-Tool v2.0: A Tool for Product Line Architecture Design Optimization. In: SIMPÓSIO BRASILEIRO DE ENGENHARIA DE SOFTWARE (SBES), 34. , 2020, Natal. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2020 .